Difference between revisions of "Opening the black box of design computation"
Abel Maciel (talk | contribs) |
Abel Maciel (talk | contribs) |
||
| (5 intermediate revisions by the same user not shown) | |||
| Line 3: | Line 3: | ||
[[Category:DCIO Proceedings]] | [[Category:DCIO Proceedings]] | ||
[[Category:Conferences]] | [[Category:Conferences]] | ||
| + | [[DC I/O 2020]] keynote by [https://orcid.org/0000-0002-0529-2116 SEAN HANNA]. | ||
| − | |||
| + | =Abstract= | ||
Looking back, in the age of BIM, at an architectural or engineering drawing from a century ago, you are likely to be struck by how little information it seems to carry. The sometimes beautiful and painstakingly rendered images themselves may be elaborate, with detail that would rank high in Shannon entropy as measured by an image compression algorithm, for instance, but in terms of providing instructions to put a building together much often seems to be left out. It seems a simpler time, without the raft of large-scale details and data, sections and specifications that we might now expect, yet how could one even consider construction of something as complicated as a contemporary building without the wealth of information these provide? | Looking back, in the age of BIM, at an architectural or engineering drawing from a century ago, you are likely to be struck by how little information it seems to carry. The sometimes beautiful and painstakingly rendered images themselves may be elaborate, with detail that would rank high in Shannon entropy as measured by an image compression algorithm, for instance, but in terms of providing instructions to put a building together much often seems to be left out. It seems a simpler time, without the raft of large-scale details and data, sections and specifications that we might now expect, yet how could one even consider construction of something as complicated as a contemporary building without the wealth of information these provide? | ||
| Line 13: | Line 14: | ||
=Reference= | =Reference= | ||
DOI: https://doi.org/10.47330/DCIO.2020.ULBU4970 | DOI: https://doi.org/10.47330/DCIO.2020.ULBU4970 | ||
| + | |||
| + | Video Presentation: https://youtu.be/amd0sa46Qvs | ||
Full text in: [https://www.designcomputation.org/dcio2020 Maciel, A. (Ed.), 2020. Design Computation Input/Output 2020, 1st ed. Design Computation, London, UK. ISBN: 978-1-83812-940-8, DOI:10.47330/DCIO.2020.QPRF9890] | Full text in: [https://www.designcomputation.org/dcio2020 Maciel, A. (Ed.), 2020. Design Computation Input/Output 2020, 1st ed. Design Computation, London, UK. ISBN: 978-1-83812-940-8, DOI:10.47330/DCIO.2020.QPRF9890] | ||
Latest revision as of 01:03, 21 January 2021
DC I/O 2020 keynote by SEAN HANNA.
Abstract
Looking back, in the age of BIM, at an architectural or engineering drawing from a century ago, you are likely to be struck by how little information it seems to carry. The sometimes beautiful and painstakingly rendered images themselves may be elaborate, with detail that would rank high in Shannon entropy as measured by an image compression algorithm, for instance, but in terms of providing instructions to put a building together much often seems to be left out. It seems a simpler time, without the raft of large-scale details and data, sections and specifications that we might now expect, yet how could one even consider construction of something as complicated as a contemporary building without the wealth of information these provide?
Keywords
DC I/O 2020, BIM, Architecture, AI.
Reference
DOI: https://doi.org/10.47330/DCIO.2020.ULBU4970
Video Presentation: https://youtu.be/amd0sa46Qvs
